The present invention relates to methods of generating and decoding watermarks robust against local and global geometric distortions (such as random bending and affine transforms) and projective transforms whose main use is copyright protection of digital media such as images, video and digital cinema.
The increasing demands of digital copyright protection market require adequate technologies able to resist against many unintentional and intentional attacks. The digital watermarking, as a means of detection and tracing of copyright violations, is the most attractive scenario accepted by many researchers and companies.
One problem with almost all current watermarking technologies is that they fail to recover a watermark from random bending geometrical distortions, known as the random bending attack (RBA). The RBA was first introduced by F. Petitcolas et al in the benchmarking tool Stirmark to model printing/scanning artifacts (F. A. P. Petitcolas, R. J. Anderson, M. G. Kuhn. Attacks on copyright marking systems, in David Aucsmith (Ed), Information Hiding, Second International Workshop, IH'98, Portland, Oreg., U.S.A., Apr. 15-17, 1998, Proceedings, LNCS 1525, Springer-Verlag, ISBN 3-540-65386-4, pp. 219-239, the content of which is incorporated herein by reference thereto). Although today's watermarking technologies are resistant against printing/scanning, unfortunately the RBA attack still remains an essential problem for almost all existing watermarking methods. The practical danger of this attack is the fact that the attacker can apply it against some watermarking technologies using the Stirmark benchmarking tool, while preserving visual image quality. Having removed the watermark, the attacker can commercially exploit the attacked image, therefore violating copyright laws.
For further background information, see M. Barni, F. Bartolini, V. Cappellini and A. Piva, “Metodo e sistema di marchiatura o cosiddetto watermarking di immagini digitali” (“A method and a system for digital image watermarking”), Italian Patent FI99A000090, filed April 1999, and M. Barni, F. Bartolini, V. Cappellini, A. De Rosa and A. Piva, “Metodo di rivelazione di un marchio in immagini digitalis” (“A method for detecting watermarks in digital images”), Italian Patent FI99A000091, filed April 1999, the contents of which is incorporated herein by reference thereto.
The main difficulty in dealing with the RBA comes from the basic assumption that all geometrical alterations introduced by the attacker are modeled as a global affine transform. This does not hold for the RBA where the introduced distortions cannot be described using only the parameters of a global affine transform. Moreover, the situation is complicated by the fact that many technologies (S. Pereira and T. Pun, “Fast Robust Template Matching for Affine Resistant Watermarks”, Lecture Notes in Computer Science: Third International Workshop on Information Hiding, Springer, vol. 1768, pp. 199-210, 1999, Italian Patent FI99A000090, filed April, 1999, Italian Patent FI99A000091, filed April 1999, Patent WO 96/36163 PCT/US96/06618, November 1996, the contents of which are incorporated herein by reference thereto) are using a global template in the magnitude spectrum of the image, which does not allow the differentiation of local alterations introduced in the case of RBA.
Several methods use the assumption about the local character of the RBA (P. Bas, J. M. Chassery and B. Maco, “Robust watermarking based on the warping of predefined regular triangular patterns”, Proceedings of SPIE: Security and Watermarking of Multimedia Content II, San Jose, Calif., U.S.A., January 2000, the content of which is incorporated herein by reference thereto). However, an exhaustive search is used to recover from this attack. Moreover, no dedicated synchronization structure for the estimation of local distortions is proposed in the above methods, except for exhaustive search solutions. This severely hampers the usage of such methods in commercial and on-line applications due to the high computational complexity of the exhaustive approach. One way to overcome this problem is to divide the image into segments or cells, and to embed the watermark into each segment. This has been done by Rhoads (Patent WO 96/36163 PCT/US96/06618, November 1996), by Lin et al (96/36163 PCT/US96/06618, November 1996 (see C. Lin, M. Wu, J. A. Bloom, I. J. Cox, M. L. Miller, Y. M. Lui, “Rotation, Scale, and Translation Resilient Public Watermarking for Images”, Proceedings of SPIE: Security and Watermarking of Multimedia Contents II, vol. 3971, pp. 90-98, San Jose, Calif., U.S.A., January 2000) as well as by Voloshynovskiy et al (S. Voloshynovskiy, F. Deguillaume and T. Pun, 2000), the contents of which are incorporated herein by reference hereto. A particular example of the use of this approach to watermark generation is the periodical tiling of the same watermark. In fact the idea of repeating the same watermark has several advantages. First, it provides resistance against cropping. Secondly, by exploiting the periodical structure of the watermark, one can use either the autocorrelation function (ACF) (M. Kutter, “Watermarking resistant to translation, rotation and scaling”, SPIE International Symposium on Voice, Video, and Data Communication, November 1998) or the magnitude spectrum of the Fourier transform (S. Voloshynovskiy, F. Deguillaume and T. Pun, 2000) to estimate and recover from global transformations. Unfortunately, all these schemes have a significant disadvantage that local random bending alterations and the general class of projective transformations are not integrated in the watermark detector.
The main concept of repetitive watermarking algorithms is based on the fact that if some geometrical transform is applied to the image, each pixel of the image is treated as having the same distortions as the remaining pixels over the whole image. However, the global ACF function or magnitude spectrum are not able to estimate the parameters of RBA. Moreover, there exist two additional typical attacks that are not covered by the global affine model of geometric transforms, namely the general class of projective transforms and local warpings. FIG. 1 illustrates typical local non-linear and global attacks that cannot be described using affine transform.
Therefore, what is needed is a method of Digital Watermarking that does not rely on the global affine model of geometrical transforms and thus protects against local and global Geometrical Distortions and Projective Transforms.